Evidence map›Paper›PMID 36166230›Full record

ArticleJAMA network open2022

County-Level Social Vulnerability and Breast, Cervical, and Colorectal Cancer Screening Rates in the US, 2018.

Cici Bauer, Kehe Zhang, Qian Xiao, Jiachen Lu, Young-Rock Hong, Ryan Suk

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  5. Examining the Role of the Social Vulnerability Index in the Association between Race/Ethnicity and Breast Cancer Outcomes.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Cici BauerDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, Houston.
Kehe ZhangDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, Houston.
Qian XiaoDepartment of Epidemiology, Human Genetics and Environmental Health, The University of Texas Health Science Center at Houston School of Public Health, Houston.
Jiachen LuDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, Houston.
Young-Rock HongDepartment of Health Services Research, Management and Policy, College of Public Health and Health Professions, University of Florida, Gainesville.
Ryan SukDepartment of Management, Policy and Community Health, The University of Texas Health Science Center at Houston School of Public Health, Houston.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Area-level factors have been identified as important social determinants of health (SDoH) that impact many health-related outcomes. Less is known about how the social vulnerability index (SVI), as a scalable composite score, can multidimensionally explain the population-based cancer screening program uptake at a county level. Objective: To examine the geographic variation of US Preventive Services Task Force (USPSTF)-recommended breast, cervical, and colorectal cancer screening rates and the association between county-level SVI and the 3 screening rates. Design, Setting, and Participants: This population-based cross-sectional study used county-level information from the Centers for Disease Control and Prevention's PLACES and SVI data sets from 2018 for 3141 US counties. Analyses were conducted from October 2021 to February 2022. Exposures: Social vulnerability index score categorized in quintiles. Main Outcomes and Measures: The main outcome was county-level rates of USPSTF guideline-concordant, up-to-date breast, cervical, and colorectal screenings. Odds ratios were calculated for each cancer screening by SVI quintile as unadjusted (only accounting for eligible population per county) or adjusted for urban-rural status, percentage of uninsured adults, and primary care physician rate per 100 000 residents. Results: Across 3141 counties, county-level cancer screening rates showed regional disparities ranging from 54.0% to 81.8% for breast cancer screening, from 69.9% to 89.7% for cervical cancer screening, and from 39.8% to 74.4% for colorectal cancer screening. The multivariable regression model showed that a higher SVI was significantly associated with lower odds of cancer screening, with the lowest odds in the highest SVI quintile. When comparing the highest quintile of SVI (SVI-Q5) with the lowest quintile of SVI (SVI-Q1), the unadjusted odds ratio was 0.86 (95% posterior credible interval [CrI], 0.84-0.87) for breast cancer screening, 0.80 (95% CrI, 0.79-0.81) for cervical cancer screening, and 0.72 (95% CrI, 0.71-0.73) for colorectal cancer screening. When fully adjusted, the odds ratio was 0.92 (95% CrI, 0.90-0.93) for breast cancer screening, 0.87 (95% CrI, 0.86-0.88) for cervical cancer screening, and 0.86 (95% CrI, 0.85-0.88) for colorectal cancer screening, showing slightly attenuated associations. Conclusions and Relevance: In this cross-sectional study, regional disparities were found in cancer screening rates at a county level. Quantifying how SVI associates with each cancer screening rate could provide insight into the design and focus of future interventions targeting cancer prevention disparities.

Indexed as

Breast NeoplasmsColorectal NeoplasmsUterine Cervical NeoplasmsAdultCross-Sectional StudiesEarly Detection of CancerFemaleHumansSocial Vulnerability

Identifiers

PMID36166230
PMCPMC9516325

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.